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Fig. 9. Trends of condition indicators analyzed by the ground station software after maintenance.
developed by Shanghai Aero Measurement-Control Technology
Research Institute have also been equipped on different
helicopters in China. With growing concern for aviation safety
and maintenance costs, many more organizations will get involved
in HUMS research and bring vigor and vitality into
HUMS in China. However, the long-term effectiveness of the
HX-HUMS needs to be confirmed in the future, including the
recently developed sparsity-assisted vibration signal processing
algorithm. Seeded fault tests should be carried out to
support the condition assessment and fault diagnosis of the
major components. More cases on board should be analyzed
comprehensively to improve the performance of the signal
processing algorithm. Moreover, with the development of highspeed
microprocessor technology, signal processing technology
and system integration technology, more powerful and efficient
functionality can be integrated in the future HUMS system.
Acknowledgment
This work was partly supported by the National Natural Science
Foundation of China under Grant Nos. 92060302 and
52122504, the National Key Research and Development
Program of China (Grant No. 2018YFB1702400), and the Fundamental
Research Funds for the Central Universities.
References
[1] " Annual safety review 2020, " European Union Aviation Safety
Agency, 2020.
[2] " Helicopter vibration health monitoring (VHM) guidance
material for operators utilizing VHM in rotor and rotor drive
systems of helicopters, " Civil Aviation Authority, CAP 753, June
2006.
April 2022
[3] E. Bechhoefer and M. Kingsley, " A review of time synchronous
average algorithms, " in Proc. Ann. Conf. PHM Soc., 2009.
[4] P. D. Samuel and D. J. Pines, " A review of vibration-based
techniques for helicopter transmission diagnostics, " J. Sound
Vibration, vol. 282, pp. 475-508, 2005.
Shibin Wang (wangshibin2008@gmail.com) is a Professor in the
School of Mechanical Engineering, Xi'an Jiaotong University,
Xi'an, China, where he received the Ph.D. degree in mechanical
engineering in 2015. His research interests include time-frequency
analysis and sparsity-assisted signal processing for
machine condition monitoring and fault diagnosis. In 2017, he
was a Visiting Scholar with the Tandon School of Engineering,
New York University, NY, USA. Previously, he received the B.S.
and M.S. degrees in electrical engineering from Soochow University,
Suzhou, China, in 2008 and 2011, respectively.
Chaowei Tong (tongchaowei@foxmail.com) received the B.S.
and Ph.D. degrees in mechanical engineering from Xi'an Jiaotong
University, China in 2014 and 2021. His research interests
include time-frequency analysis, sparse representation and
signal processing in machine condition monitoring and fault
diagnosis.
Zhiyu Tao (taoyushi1@163.com) is the Deputy General Manager
of the Research and Development Center of Guangzhou
Hangxin Aviation Technology Co., Ltd. He is also the Chief
Engineer of HUMS in Hangxin and is responsible for the overall
design, data analysis and technical support of HUMS. He
received the M.B.A. degree from the Northwestern Polytechnical
University, Xi'an, China in 2002.
IEEE Instrumentation & Measurement Magazine
51

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